As simulated training becomes ever more important, significant effort has gone into creating and improving simulated training systems. In particular, to provide effective combat training, a premium is placed on target tracking, because without precise target tracking, the value of any training is diminished, since the trainee cannot ascertain accurately whether various techniques provide improved aim.
In the past, many approaches have been used to provide target tracking. Merely by way of example, some systems have used video cameras to provide target tracking. Some such systems, for instance, used the luminance and/or chromance of a video imaged to determine where in a video image a target appears. Such systems may calculate a centroid for the image, for instance by reference to a region defined by matching chromance and/or luminance to pattern values, which might match patterns for flesh tones and/or other applicable patterns. Another type of video tracking system relies on a specified window to isolate regions of interest in order to determine a target. Analog comparison techniques may be used to perform tracking.
In yet another system, a live digitized image is compared with a digitized background image. Based on pixel differences, a centroid for a center of mass of a differenced image is calculated. Velocity of the differenced image may be computed using video frame differences. Other systems use correlation between gated regions on successive frames to match location on a moving region.
Yet another set of tracking systems utilize digital space correlation to suppress false target signals as applied to a point target tracking device. The search field of a tracking system is divided into a matrix of rows and columns of elemental fields of view. Each elemental field view is examined to determine if a target exists in that field and matrix neighbors are compared to determine if target signal exist in adjacent elemental fields. The system rejects a signal if its adjacent matrix neighbor contains a signal.
In some tracking systems, a video processor is coupled to the television camera and limits the system response to signals representative of the inner intensity contour of possible targets. A digital processor responds to the video processor output signals to determine the difference between the angular location of the designated object and a previously stored estimate of this position and then updates the stored position. The updating function is normalized by the target image dimension so that the tracking response of the system is essentially independent of the target image size. The video processor unit eliminates signals which are not representative of a designated target on the basis of signal amplitude comparisons. Digital logic circuits distinguish between the design target and false targets on the basis of angular location.
Such systems, however, fail to provide sufficient precision in determining targets, especially in tracking a target of interest in a field of multiple targets. Further, conventional systems have difficulty effectively predicting the position of targets, especially during periods of intense motion.